






"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


__SCREAMING_SNAKE_CASE   =   logging.get_logger(__name__)




class 						__UpperCamelCase     (     UpperCamelCase						):
					lowercase_    :				int      =  """timm_backbone"""
					def __init__(							self							:	Any     , UpperCAmelCase							:	Tuple=None     , UpperCAmelCase							:	Dict=3     , UpperCAmelCase							:	Optional[int]=True     , UpperCAmelCase							:	Dict=True     , UpperCAmelCase							:	str=None     , **UpperCAmelCase							:	Union[str, Any]     , )	->       List[Any]:
											super().__init__(**UpperCAmelCase   )
											lowerCAmelCase   :Union[str, Any]						=			backbone
											lowerCAmelCase   :Any						=			num_channels
											lowerCAmelCase   :Optional[Any]						=			features_only
											lowerCAmelCase   :Union[str, Any]						=			use_pretrained_backbone
											lowerCAmelCase   :Union[str, Any]						=			True
											lowerCAmelCase   :Dict						=			out_indices if out_indices is not None else (-1,)







"""simple docstring"""


import unittest

from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken

from ...test_tokenization_common import TokenizerTesterMixin


__SCREAMING_SNAKE_CASE   =   get_tests_dir('fixtures/test_sentencepiece_bpe_char.model')




@require_sentencepiece
@require_tokenizers
class 						__UpperCamelCase     (     UpperCamelCase   ,     unittest.TestCase						):
					lowercase_    :				Optional[int]      =  SpeechTaTokenizer
					lowercase_    :				Dict      =  False
					lowercase_    :				Any      =  True
					def        UpperCAmelCase__ (							self							:	Tuple   )	->       Optional[Any]:
											super().setUp()

											# We have a SentencePiece fixture for testing
											lowerCAmelCase   :Union[str, Any]						=			SpeechTaTokenizer(UpperCAmelCase   )

											lowerCAmelCase   :Any						=			AddedToken('<mask>'     , lstrip=UpperCAmelCase     , rstrip=UpperCAmelCase   )
											lowerCAmelCase   :List[Any]						=			mask_token
											tokenizer.add_special_tokens({'mask_token': mask_token}   )
											tokenizer.add_tokens(['<ctc_blank>']   )

											tokenizer.save_pretrained(self.tmpdirname   )
					def        UpperCAmelCase__ (							self							:	str     , UpperCAmelCase							:	Any   )	->       Union[str, Any]:
											lowerCAmelCase   :Tuple						=			'this is a test'
											lowerCAmelCase   :Union[str, Any]						=			'this is a test'
											return input_text, output_text
					def        UpperCAmelCase__ (							self							:	Optional[Any]     , UpperCAmelCase							:	Optional[int]     , UpperCAmelCase							:	Any=False     , UpperCAmelCase							:	List[Any]=20     , UpperCAmelCase							:	str=5   )	->       Optional[Any]:
											lowerCAmelCase	, lowerCAmelCase   :Dict						=			self.get_input_output_texts(UpperCAmelCase   )
											lowerCAmelCase   :str						=			tokenizer.encode(UpperCAmelCase     , add_special_tokens=UpperCAmelCase   )
											lowerCAmelCase   :Union[str, Any]						=			tokenizer.decode(UpperCAmelCase     , clean_up_tokenization_spaces=UpperCAmelCase   )
											return text, ids
					def        UpperCAmelCase__ (							self							:	Any   )	->       Optional[Any]:
											lowerCAmelCase   :List[Any]						=			'<pad>'
											lowerCAmelCase   :Any						=			1

											self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase   )     , UpperCAmelCase   )
											self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase   )     , UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	Any   )	->       Any:
											lowerCAmelCase   :Dict						=			list(self.get_tokenizer().get_vocab().keys()   )

											self.assertEqual(vocab_keys[0]     , '<s>'   )
											self.assertEqual(vocab_keys[1]     , '<pad>'   )
											self.assertEqual(vocab_keys[-4]     , 'œ'   )
											self.assertEqual(vocab_keys[-2]     , '<mask>'   )
											self.assertEqual(vocab_keys[-1]     , '<ctc_blank>'   )
											self.assertEqual(len(UpperCAmelCase   )     , 81   )
					def        UpperCAmelCase__ (							self							:	Tuple   )	->       Union[str, Any]:
											self.assertEqual(self.get_tokenizer().vocab_size     , 79   )
					def        UpperCAmelCase__ (							self							:	Any   )	->       List[str]:
											lowerCAmelCase   :Any						=			self.get_tokenizers(do_lower_case=UpperCAmelCase   )
											for tokenizer in tokenizers:
																	with self.subTest(f"""{tokenizer.__class__.__name__}"""   ):
																							lowerCAmelCase   :Optional[int]						=			tokenizer.vocab_size
																							lowerCAmelCase   :Union[str, Any]						=			len(UpperCAmelCase   )

																							self.assertNotEqual(UpperCAmelCase     , 0   )

																							# We usually have added tokens from the start in tests because our vocab fixtures are
																							# smaller than the original vocabs - let's not assert this
																							# self.assertEqual(vocab_size, all_size)

																							lowerCAmelCase   :Optional[Any]						=			['aaaaa bbbbbb', 'cccccccccdddddddd']
																							lowerCAmelCase   :Union[str, Any]						=			tokenizer.add_tokens(UpperCAmelCase   )
																							lowerCAmelCase   :str						=			tokenizer.vocab_size
																							lowerCAmelCase   :List[Any]						=			len(UpperCAmelCase   )

																							self.assertNotEqual(UpperCAmelCase     , 0   )
																							self.assertEqual(UpperCAmelCase     , UpperCAmelCase   )
																							self.assertEqual(UpperCAmelCase     , len(UpperCAmelCase   )   )
																							self.assertEqual(UpperCAmelCase     , all_size + len(UpperCAmelCase   )   )

																							lowerCAmelCase   :int						=			tokenizer.encode('aaaaa bbbbbb low cccccccccdddddddd l'     , add_special_tokens=UpperCAmelCase   )

																							self.assertGreaterEqual(len(UpperCAmelCase   )     , 4   )
																							self.assertGreater(tokens[0]     , tokenizer.vocab_size - 1   )
																							self.assertGreater(tokens[-3]     , tokenizer.vocab_size - 1   )

																							lowerCAmelCase   :List[Any]						=			{'eos_token': '>>>>|||<||<<|<<', 'pad_token': '<<<<<|||>|>>>>|>'}
																							lowerCAmelCase   :str						=			tokenizer.add_special_tokens(UpperCAmelCase   )
																							lowerCAmelCase   :Optional[Any]						=			tokenizer.vocab_size
																							lowerCAmelCase   :Tuple						=			len(UpperCAmelCase   )

																							self.assertNotEqual(UpperCAmelCase     , 0   )
																							self.assertEqual(UpperCAmelCase     , UpperCAmelCase   )
																							self.assertEqual(UpperCAmelCase     , len(UpperCAmelCase   )   )
																							self.assertEqual(UpperCAmelCase     , all_size_a + len(UpperCAmelCase   )   )

																							lowerCAmelCase   :List[str]						=			tokenizer.encode(
																							    '>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l'     , add_special_tokens=UpperCAmelCase   )

																							self.assertGreaterEqual(len(UpperCAmelCase   )     , 6   )
																							self.assertGreater(tokens[0]     , tokenizer.vocab_size - 1   )
																							self.assertGreater(tokens[0]     , tokens[1]   )
																							self.assertGreater(tokens[-3]     , tokenizer.vocab_size - 1   )
																							self.assertGreater(tokens[-3]     , tokens[-4]   )
																							self.assertEqual(tokens[0]     , tokenizer.eos_token_id   )
																							self.assertEqual(tokens[-3]     , tokenizer.pad_token_id   )
					def        UpperCAmelCase__ (							self							:	Union[str, Any]   )	->       Optional[Any]:
											pass
					def        UpperCAmelCase__ (							self							:	str   )	->       int:
											pass
					def        UpperCAmelCase__ (							self							:	Optional[int]   )	->       List[Any]:
											lowerCAmelCase   :Optional[int]						=			self.get_tokenizer()

											lowerCAmelCase   :List[str]						=			tokenizer.tokenize('This is a test'   )
											# fmt: off
											self.assertListEqual(UpperCAmelCase     , [SPIECE_UNDERLINE, 'T', 'h', 'i', 's', SPIECE_UNDERLINE, 'i', 's', SPIECE_UNDERLINE, 'a', SPIECE_UNDERLINE, 't', 'e', 's', 't']   )
											# fmt: on

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(UpperCAmelCase   )     , [4, 32, 11, 10, 12, 4, 10, 12, 4, 7, 4, 6, 5, 12, 6]     , )

											lowerCAmelCase   :List[str]						=			tokenizer.tokenize('I was born in 92000, and this is falsé.'   )
											self.assertListEqual(
											    UpperCAmelCase     , [SPIECE_UNDERLINE, 'I', SPIECE_UNDERLINE, 'w', 'a', 's', SPIECE_UNDERLINE, 'b', 'o', 'r', 'n', SPIECE_UNDERLINE, 'i', 'n', SPIECE_UNDERLINE, '92000', ',', SPIECE_UNDERLINE, 'a', 'n', 'd', SPIECE_UNDERLINE, 't', 'h', 'i', 's', SPIECE_UNDERLINE, 'i', 's', SPIECE_UNDERLINE, 'f', 'a', 'l', 's', 'é', '.']   )

											lowerCAmelCase   :Optional[int]						=			tokenizer.convert_tokens_to_ids(UpperCAmelCase   )
											# fmt: off
											self.assertListEqual(UpperCAmelCase     , [4, 30, 4, 20, 7, 12, 4, 25, 8, 13, 9, 4, 10, 9, 4, 3, 23, 4, 7, 9, 14, 4, 6, 11, 10, 12, 4, 10, 12, 4, 19, 7, 15, 12, 73, 26]   )
											# fmt: on

											lowerCAmelCase   :int						=			tokenizer.convert_ids_to_tokens(UpperCAmelCase   )
											self.assertListEqual(
											    UpperCAmelCase     , [SPIECE_UNDERLINE, 'I', SPIECE_UNDERLINE, 'w', 'a', 's', SPIECE_UNDERLINE, 'b', 'o', 'r', 'n', SPIECE_UNDERLINE, 'i', 'n', SPIECE_UNDERLINE, '<unk>', ',', SPIECE_UNDERLINE, 'a', 'n', 'd', SPIECE_UNDERLINE, 't', 'h', 'i', 's', SPIECE_UNDERLINE, 'i', 's', SPIECE_UNDERLINE, 'f', 'a', 'l', 's', 'é', '.']   )
					@slow
					def        UpperCAmelCase__ (							self							:	str   )	->       Tuple:
											# Use custom sequence because this tokenizer does not handle numbers.
											lowerCAmelCase   :Any						=			[
											    'Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '
											    'general-purpose architectures (BERT, GPT, RoBERTa, XLM, DistilBert, XLNet...) for Natural '
											    'Language Understanding (NLU) and Natural Language Generation (NLG) with over thirty-two pretrained '
											    'models in one hundred plus languages and deep interoperability between Jax, PyTorch and TensorFlow.',
											    'BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '
											    'conditioning on both left and right context in all layers.',
											    'The quick brown fox jumps over the lazy dog.',
											]

											# fmt: off
											lowerCAmelCase   :List[str]						=			{
											    'input_ids': [
											        [4, 32, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 64, 19, 8, 13, 18, 5, 13, 15, 22, 4, 28, 9, 8, 20, 9, 4, 7, 12, 4, 24, 22, 6, 8, 13, 17, 11, 39, 6, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 7, 9, 14, 4, 24, 22, 6, 8, 13, 17, 11, 39, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 39, 25, 5, 13, 6, 63, 4, 24, 13, 8, 27, 10, 14, 5, 12, 4, 21, 5, 9, 5, 13, 7, 15, 39, 24, 16, 13, 24, 8, 12, 5, 4, 7, 13, 17, 11, 10, 6, 5, 17, 6, 16, 13, 5, 12, 4, 64, 40, 47, 54, 32, 23, 4, 53, 49, 32, 23, 4, 54, 8, 40, 47, 54, 32, 7, 23, 4, 69, 52, 43, 23, 4, 51, 10, 12, 6, 10, 15, 40, 5, 13, 6, 23, 4, 69, 52, 48, 5, 6, 26, 26, 26, 63, 4, 19, 8, 13, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 61, 9, 14, 5, 13, 12, 6, 7, 9, 14, 10, 9, 21, 4, 64, 48, 52, 61, 63, 4, 7, 9, 14, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 53, 5, 9, 5, 13, 7, 6, 10, 8, 9, 4, 64, 48, 52, 53, 63, 4, 20, 10, 6, 11, 4, 8, 27, 5, 13, 4, 6, 11, 10, 13, 6, 22, 39, 6, 20, 8, 4, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 4, 18, 8, 14, 5, 15, 12, 4, 10, 9, 4, 8, 9, 5, 4, 11, 16, 9, 14, 13, 5, 14, 4, 24, 15, 16, 12, 4, 15, 7, 9, 21, 16, 7, 21, 5, 12, 4, 7, 9, 14, 4, 14, 5, 5, 24, 4, 10, 9, 6, 5, 13, 8, 24, 5, 13, 7, 25, 10, 15, 10, 6, 22, 4, 25, 5, 6, 20, 5, 5, 9, 4, 58, 7, 37, 23, 4, 49, 22, 32, 8, 13, 17, 11, 4, 7, 9, 14, 4, 32, 5, 9, 12, 8, 13, 55, 15, 8, 20, 26, 2],
											        [4, 40, 47, 54, 32, 4, 10, 12, 4, 14, 5, 12, 10, 21, 9, 5, 14, 4, 6, 8, 4, 24, 13, 5, 39, 6, 13, 7, 10, 9, 4, 14, 5, 5, 24, 4, 25, 10, 14, 10, 13, 5, 17, 6, 10, 8, 9, 7, 15, 4, 13, 5, 24, 13, 5, 12, 5, 9, 6, 7, 6, 10, 8, 9, 12, 4, 19, 13, 8, 18, 4, 16, 9, 15, 7, 25, 5, 15, 5, 14, 4, 6, 5, 37, 6, 4, 25, 22, 4, 46, 8, 10, 9, 6, 15, 22, 4, 17, 8, 9, 14, 10, 6, 10, 8, 9, 10, 9, 21, 4, 8, 9, 4, 25, 8, 6, 11, 4, 15, 5, 19, 6, 4, 7, 9, 14, 4, 13, 10, 21, 11, 6, 4, 17, 8, 9, 6, 5, 37, 6, 4, 10, 9, 4, 7, 15, 15, 4, 15, 7, 22, 5, 13, 12, 26, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
											        [4, 32, 11, 5, 4, 45, 16, 10, 17, 28, 4, 25, 13, 8, 20, 9, 4, 19, 8, 37, 4, 46, 16, 18, 24, 12, 4, 8, 27, 5, 13, 4, 6, 11, 5, 4, 15, 7, 57, 22, 4, 14, 8, 21, 26, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
											    ],
											    'attention_mask': [
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											}
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=UpperCAmelCase     , model_name='microsoft/speecht5_asr'     , revision='c5ef64c71905caeccde0e4462ef3f9077224c524'     , sequences=UpperCAmelCase     , )